A user of a client device relies on one or more dictionaries of words for spell checking, suggesting words during typing, and other uses of known words. When suggesting words, emojis, deep links, and other terms to a user, the user would often like the most frequently used terms to be presented toward the top of a list of such suggestions. In the prior art, dictionaries typically use a fixed ordering of terms suggestions. If ordering is changed at all based on usage, the ordering of suggestions is based on only the local usage on a client of terms.
Current servers can learn the frequency of the words that users type by examining the clear text that a large plurality of users have typed that is received by a server (“crowdsourced data”). For example, some text message services and email services (collectively, messages) receive messages in clear text and the servers can analyze the messages. Applications that run on a client device, e.g. Yelp!®, can send a uniform resource locator (URL) as clear text to a server. The server can learn the frequency with which users select the link by reading the clear text of the link received in the crowdsourced data. The servers can read the clear text of deep links, emojis, and words obtained received from user client devices. However the server does not update the users' dictionaries, asset catalog, or applications to provide the client device with the most frequently selected emojis, deep links and words at the top of a list of such terms.
In addition, current servers' use of the clear text in user messages compromises the privacy of users. Some applications on mobile devices currently share location data with servers to help the user obtain results that are relevant to the user's location. Some applications, such as web browsers, track a user's location using an internet protocol (IP) address, cell tower location, WiFi router address and network name (which may literally identify the business or user that owns the router), or other location tracking means. Servers store clear text of a user's queries to the server. Servers can also store feedback data indicating which links a user selected, and any queries that followed a selection. Servers can also track the dwell time that a user looks at content presented to the user. Further, server owners sell and share information with one another. For example, a social network may sell user information and preferences to content providers so that the content providers can push content deemed relevant to the user, based upon the user information, location information, and clear text from the user that is collected by the server. In combination, these information sources can identify a particular computer, or user, with reasonable specificity, compromising the privacy of the user.